In the age of deepfakes, some people are using tactics like asking rapid-fire questions or sharing code words with each other to verify every online interaction
As AI-driven fraud becomes increasingly common, more people feel the need to verify every interaction they have online.
Context & Ripple Effects
Earlier coverage traced the credibility problem from election-related deepfake misuse to AI-generated text that can blend into ordinary social chatter. The concern has broadened beyond obviously altered video or audio.
By 2023, creators were already being asked to prove they were human as synthetic media improved. This story shows that burden moving into routine person-to-person online contact.
First-order effects
- People who suspect AI-enabled impersonation are adding ad hoc verification steps—such as rapid questions and shared code words—before treating an online interaction as genuine.
- Routine online communication becomes slower and more conditional for both the person seeking proof and the person being asked to provide it.
Second-order effects
- These informal checks raise the cost of simple impersonation, but also shift fraud defense onto individuals rather than a single platform or service.
- The pattern increases the practical value of identity and authenticity checks in workflows where an unverified message, voice, or image could trigger action.
Third-order effects
- If such habits persist, online trust may increasingly depend on repeatable verification rituals rather than on the apparent realism of content alone.
- That shift would reinforce demand for proof-of-personhood and workflow-level assurance, while leaving open whether informal social methods can scale across high-volume interactions.
The trend: This is one instance of trust moving from content recognition toward active verification as synthetic media becomes harder to distinguish from human communication.